An Update on Endocrine Mucin-producing Sweat Gland Carcinoma
Bibliographic record
Abstract
Endocrine mucin-producing sweat gland carcinoma (EMPSGC) is a rare, low-grade adnexal neoplasm with predilection for the periorbital skin of older women. Histologically and immunophenotypically, EMPSGC is analogous to another neoplasm with neuroendocrine differentiation, solid papillary carcinoma of the breast. Both lesions are spatially associated with neuroendocrine mucinous adenocarcinomas of the skin and breast, respectively. EMPSGC is ostensibly a precursor of neuroendocrine-type mucinous sweat gland adenocarcinoma (MSC), a lesion of uncertain prognosis. Non-neuroendocrine MSC has been deemed locally aggressive with metastatic potential, and previous works speculated that EMPSGC-associated (neuroendocrine-type) MSC had similar recurrence and metastatic potential with implications for patient follow-up. Only 96 cases of EMPSGC have been reported (12 cases in the largest case series). Herein, we present 63 cases diagnosed as "EMPSGC" in comparison with aggregated results from known published EMPSGC cases. We aim to clarify the clinicopathologic features and prognostic significance of the neuroendocrine differentiation of EMPSGC and its associated adenocarcinoma and to determine the nosological relevance of EMPSGC association in the spectrum of MSC histopathogenesis. Results established an overall female predominance (66.7%) and average presenting age of 64 years. EMPSGC lesions were associated with adjacent MSC in 33.3% of cases. The recurrence rate for neuroendocrine-type MSC was ~21%, less than the reported 30% for non-neuroendocrine MSC. There were no cases of metastasis. EMPSGC and neuroendocrine-type MSC are distinct entities with more indolent behavior than previously reported, supporting a favorable prognosis for patients.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.003 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".